{"title":"A deep learning and statistical shape modeling-based method for assessing intercondylar notch volume in anterior cruciate ligament reconstruction","authors":"Anna Ghidotti , Daniele Regazzoni , Miri Weiss Cohen , Caterina Rizzi , Vincenzo Condello","doi":"10.1016/j.knee.2025.02.009","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><div>Anterior cruciate ligament (ACL) reconstruction is a widely performed procedure for ACL injury, but there are several factors which may lead to re-rupture or clinical failure. An intercondylar notch (or fossa) that is narrower may increase the likelihood of injury. Traditional two-dimensional assessments are limited, and three-dimensional (3D) volume analysis may offer more detailed insights. This study employs deep learning and statistical shape modeling (SSM) to enhance 3D modeling of the intercondylar notch, aiming to gain a deeper understanding of this complex 3D anatomical region.</div></div><div><h3>Methods</h3><div>A methodology was developed to generate accurate 3D models of the intercondylar fossa within seconds. The variability of the intercondylar notch in ACL-injured samples was analyzed using SSM techniques, focusing on its principal components. Additionally, gender differences in notch volume were examined using <em>t</em>-tests.</div></div><div><h3>Results</h3><div>The best deep learning method for automatic segmentation of the notch was SegResNet, which achieved a Dice similarity coefficient of over 0.88 and a Hausdorff distance of 0.73 mm. The small volume-related relative error (0.06) illustrates the goodness of the result. Three principal components accounted for 72.59% of the variation, including notch volume, shape, width, and height. Females had statistically significant smaller notch compared with males with ACL injury (<em>P</em> < 0.001).</div></div><div><h3>Conclusion</h3><div>By examining notch volume and its variability in ACL-injured patients, it is possible to understand the complex anatomy of the intercondylar notch and tailor ACL reconstructions accordingly.</div></div>","PeriodicalId":56110,"journal":{"name":"Knee","volume":"54 ","pages":"Pages 71-80"},"PeriodicalIF":1.6000,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Knee","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0968016025000225","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ORTHOPEDICS","Score":null,"Total":0}
引用次数: 0
Abstract
Background
Anterior cruciate ligament (ACL) reconstruction is a widely performed procedure for ACL injury, but there are several factors which may lead to re-rupture or clinical failure. An intercondylar notch (or fossa) that is narrower may increase the likelihood of injury. Traditional two-dimensional assessments are limited, and three-dimensional (3D) volume analysis may offer more detailed insights. This study employs deep learning and statistical shape modeling (SSM) to enhance 3D modeling of the intercondylar notch, aiming to gain a deeper understanding of this complex 3D anatomical region.
Methods
A methodology was developed to generate accurate 3D models of the intercondylar fossa within seconds. The variability of the intercondylar notch in ACL-injured samples was analyzed using SSM techniques, focusing on its principal components. Additionally, gender differences in notch volume were examined using t-tests.
Results
The best deep learning method for automatic segmentation of the notch was SegResNet, which achieved a Dice similarity coefficient of over 0.88 and a Hausdorff distance of 0.73 mm. The small volume-related relative error (0.06) illustrates the goodness of the result. Three principal components accounted for 72.59% of the variation, including notch volume, shape, width, and height. Females had statistically significant smaller notch compared with males with ACL injury (P < 0.001).
Conclusion
By examining notch volume and its variability in ACL-injured patients, it is possible to understand the complex anatomy of the intercondylar notch and tailor ACL reconstructions accordingly.
期刊介绍:
The Knee is an international journal publishing studies on the clinical treatment and fundamental biomechanical characteristics of this joint. The aim of the journal is to provide a vehicle relevant to surgeons, biomedical engineers, imaging specialists, materials scientists, rehabilitation personnel and all those with an interest in the knee.
The topics covered include, but are not limited to:
• Anatomy, physiology, morphology and biochemistry;
• Biomechanical studies;
• Advances in the development of prosthetic, orthotic and augmentation devices;
• Imaging and diagnostic techniques;
• Pathology;
• Trauma;
• Surgery;
• Rehabilitation.